Stephen Batifol

Developer Advocate

Stephen Batifol is a Developer Advocate at Zilliz. He previously worked as a Machine Learning Engineer at Wolt, where he was working on the ML Platform and as a Data Scientist at Brevo. Stephen studied Computer Science and Artificial Intelligence. He enjoys dancing and surfing.

Engineering

How to Use Anthropic MCP Server with Milvus

MCP + Milvus: Streamline AI agent development with standardized data access, eliminating integration hassles while enhancing context and flexibility.

Mar 14, 20254 min read

Engineering

Milvus WebUI: A Visual Management Tool for Your Vector Database

Explore Milvus WebUI to monitor, manage, and optimize your vector database with real-time insights, performance tracking, and system health monitoring.

Mar 02, 20254 min read

Engineering

Beyond PGVector: When Your Vector Database Needs a Formula 1 Upgrade

This blog explores why Postgres, with its vector search add-on, pgvector, works well for smaller projects and simpler use cases but reaches its limits for large-scale vector search.

Jan 13, 20256 min read

Engineering

Stop Waiting, Start Building: Voice Assistant With Milvus and Llama 3.2

We'll learn to build a Voice Assistant, a specialized Agentic RAG system designed for voice interactions, with Milvus, Llama 3.2, and other GenAI tools.

Nov 23, 20246 min read

Engineering

Deploying a Multimodal RAG System Using vLLM and Milvus

Multimodal RAG, Milvus vector database, vector database, retrieval augmented generation RAG

Nov 13, 20247 min read

Engineering

ColPali: Enhanced Document Retrieval with Vision Language Models and ColBERT Embedding Strategy

ColPali is an advanced document retrieval model designed to index and retrieve information directly from the visual features of documents, particularly PDFs.

Oct 12, 20247 min read

Community

Scaling Search for AI: How Milvus Outperforms OpenSearch

Explore how Milvus matches OpenSearch in speed and scalability and surpasses it with its specialized vector search capabilities

Oct 11, 20245 min read

Engineering

Building a GraphRAG Agent With Neo4j and Milvus

Build a GraphRAG Agent using Neo4j and Milvus. By combining the strengths of graph databases and vector search, this agent provides accurate and relevant answers to user queries.

Oct 01, 20247 min read

Community

Multimodal RAG: Expanding Beyond Text for Smarter AI

Multimodal RAG systems provide a comprehensive solution for leveraging the full spectrum of available information, providing better context to LLMs.

Sep 19, 20246 min read